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Call for Papers

The 6th International Conference on Social Sciences and Intelligence Management (SSIM 2026) invites original research contributions from scholars, researchers, educators, practitioners, and industry professionals worldwide.

Under the theme “Human-Centered AI, Sustainable Digital Ecosystems, and Intelligent Transformation in Social Sciences,” the conference aims to provide an interdisciplinary platform for exchanging innovative ideas, presenting cutting-edge research, and fostering international collaboration across social sciences, education, management, communication, and intelligent technologies. We welcome full papers, conceptual papers, and applied research addressing theoretical development, empirical studies, and practical applications in the following thematic tracks.

We welcome full papers, conceptual papers, and applied research addressing theoretical development, empirical studies, and practical applications in the following thematic tracks:

Detailed Conference Tracks & Topics

Track 1: Human-Centered AI and Intelligent Learning Ecosystems | File

Research on artificial intelligence in education, adaptive learning environments, intelligent tutoring systems, educational data mining, learning analytics, technology-supported pedagogy, and sustainable digital learning ecosystems.

  • Detailed Topics Include:
    • AI-powered adaptive learning platforms and personalized instruction
    • Educational data mining (EDM) and learning analytics dashboard design
    • Intelligent tutoring systems (ITS) and conversational agents in education
    • Technology-supported pedagogy and blended/flipped learning models
    • Ethical, privacy, and governance frameworks for AI in educational settings
    • Sustainable digital learning ecosystems and infrastructure development
    • Virtual classrooms, smart campuses, and institutional digital transformation

Track 2: Computational Technologies for Early Childhood Development and Interactive Learning | File

Innovative applications of AI-supported developmental assessment, music and arts-based technologies, multimodal learning analytics, sensor-based movement analysis, interactive learning environments, AI-assisted social communication evaluation, educational robotics, augmented/virtual reality (AR/VR), technology-enhanced inclusive and special education, and digital developmental frameworks for early childhood education.

  • Detailed Topics Include:
    • AI-supported assessment of language acquisition, literacy emergence, and cognitive milestones
    • Multimodal learning analytics integrating video, audio, physiological, and behavioral data streams
    • Social robots as learning companions: behavioral modeling, adaptive interaction, and affect recognition
    • Intelligent interactive learning environments: architecture, sensor fusion, and real-time adaptation
    • Augmented reality (AR) and virtual reality (VR) systems: design frameworks and developmental outcome evaluation
    • Sensor-based movement analysis for motor development assessment and physical activity monitoring
    • AI-assisted identification and support for children with autism spectrum disorder (ASD), developmental delays, or diverse learning profiles
    • Assistive technology systems: design principles, computational architectures, and accessibility evaluation
    • Music and arts-based technology systems: computational design, interaction modeling, and developmental evaluation
    • AI systems for supporting social-emotional learning (SEL): detection, modeling, and adaptive response classrooms

Track 3: Computational Approaches to Language Education, EMI, and Intelligent Communication Systems | File

Research related to English-Medium Instruction (EMI), intelligent language systems, AI-assisted language learning, computational linguistics, AI-mediated communication, digital discourse analysis, bilingual education, TESOL, intercultural/academic communication, and intelligent language assessment technologies.

  • Detailed Topics Include:
    • AI-assisted language learning platforms: architectures, algorithms, and pedagogical evaluation
    • Large language models (LLMs) in language education: affordances, limitations, and user studies
    • Computational approaches to oral proficiency assessment and speech recognition in L2 contexts
    • Cross-linguistic transfer and computational models of bilingual language processing
    • Data-driven studies of English-Medium Instruction (EMI): classroom discourse, comprehension, and outcomes
    • AI-mediated communication in multilingual and multicultural academic environments
    • AI literacy and digital competence: empirical frameworks and measurement instruments

Track 4: Intelligent Healthcare, Social Innovation, and Inclusive Technologies | File

Intelligent systems and data-driven applications in healthcare, social innovation, assistive technologies, community care systems, digital inclusion, rehabilitation technologies, and technology-supported social services.

  • Detailed Topics Include:
    • Smart healthcare systems, telehealth, and AI-driven diagnostic assistance
    • Social innovation frameworks and technology-driven social entrepreneurship
    • Assistive technologies and rehabilitative devices for the elderly and disabled
    • Data-driven community care systems and smart aging solutions
    • Digital inclusion policies and overcoming the digital divide in vulnerable groups
    • Technology-supported social work, counseling, and public social services
    • Human-robot interaction (HRI) in caregiving and healthcare environments

Track 5: Computational Media, Digital Communication, and Information Ethics | File

Research on computational media systems, algorithmic communication, misinformation detection, synthetic media analytics, digital narrative systems, media intelligence, platform governance, and ethical frameworks in intelligent communication environments.

  • Detailed Topics Include:
    • Computational journalism, automated content generation, and media intelligence
    • Algorithmic communication, recommendation systems, and echo chamber effects
    • Misinformation, deepfake, and synthetic media detection and analytics
    • Digital narrative systems, interactive storytelling, and immersive media
    • Social media analytics, sentiment analysis, and public opinion mining
    • Platform governance, digital privacy, and copyright in the era of generative AI
    • Information ethics, digital citizenship, and algorithmic fairness

Track 6: AI-Driven Business Analytics and Sustainable Governance | File

Research on AI-driven business intelligence, ESG (Environmental, Social, and Governance) analytics, digital leadership, fintech innovation, sustainable corporate governance, organizational transformation, supply-chain resilience, and strategic data analytics.

  • Detailed Topics Include:
    • AI-driven business intelligence, predictive modeling, and consumer behavior analytics
    • ESG (Environmental, Social, and Governance) data analytics and reporting systems
    • Digital leadership, remote workforce management, and organizational agility
    • Fintech innovations, blockchain applications, and smart contract governance
    • Sustainable corporate governance models in the digital transformation era
    • Data-driven supply-chain resilience and smart logistics optimization
    • Strategic decision-making based on big data analytics and machine learning

Track 7: Computational Social Sciences and Advanced Data Analytics | File

Advanced quantitative methodologies, machine learning applications, predictive analytics, behavioral modeling, structural equation modeling, panel data analysis, longitudinal computational analysis, and interdisciplinary computational approaches across the social sciences

  • Detailed Topics Include:
    • Advanced quantitative research designs and computational social science frameworks
    • Machine learning and predictive analytics for human behavior and societal trends
    • Behavioral modeling, simulation, and agent-based computational economics
    • Structural Equation Modeling (SEM) and advanced multivariate analysis
    • Panel Vector Autoregression (VAR) and dynamic econometric modeling
    • Longitudinal computational analysis of learning outcomes and social dynamics
    • Big data infrastructure, web scraping, and text mining for social science research

Submission Guidelines & Important Dates

All submissions must be original, unpublished, and written in English. Full papers submitted for the Springer CCIS volume must follow the Springer formatting guidelines (typically 12–15+ pages for full papers). All papers will pass through a strict plagiarism check (Turnitin/iThenticate) and a double-blind peer-review process by at least 3 reviewers.

  • Full Paper Submission Deadline: October 15, 2026
  • Acceptance Notification: November 20, 2026
  • Camera-Ready Paper Deadline: December 10, 2026
  • Conference Dates: December 17–19, 2026